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app-hotes:ai-features [2026/06/24 15:25] – [1. Installing the Module into the Router Hardware] grayapp-hotes:ai-features [2026/06/24 20:22] (current) – [2. Additional information] gray
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-====== Netmodule Routers with AI Features ======+====== Netmodule Routers with KI Features ======
  
 ===== Goal ===== ===== Goal =====
  
-This wiki shows how to enable an AICore DX-M1 chip in the router and use it within an LXC container. It also explains how to set up additional utilities within the container.+This wiki shows how to enable an KICore DX-M1 chip in the router and use it within an LXC container. It also explains how to set up additional utilities within the container.
  
 ===== The background to this project ===== ===== The background to this project =====
-text+Enable the router to run its own KI modules locally, directly on the router, without having to use a hyperscaler. Your own data can be used to train the AI modules because it is not shared with third parties. The entire value chain remains under your control and can be flexibly developed further. Applications include intelligent energy management systems, dynamic traffic control systems, and production management. The KI modules can be trained and fine-tuned for their core tasks to achieve optimal results.
  
 === Modules in the router=== === Modules in the router===
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 ===== - Installing the Module into the Router Hardware ===== ===== - Installing the Module into the Router Hardware =====
  
-An adapter is required for the Deepx DX-M1 AI chip to be used with the router. The PCI Express interfaces are implemented as Mini PCIe on the router board. The DX-M1 chip requires a Mini PCIe to M.2 M-key adapter.+An adapter is required for the Deepx DX-M1 KI chip to be used with the router. The PCI Express interfaces are implemented as Mini PCIe on the router board. The DX-M1 chip requires a Mini PCIe to M.2 M-key adapter.
  
 {{:app-notes:ki_adapter.jpg?900|}} {{:app-notes:ki_adapter.jpg?900|}}
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 02:00.0 Class 1200: 1ff4:0000 02:00.0 Class 1200: 1ff4:0000
 </konsole> </konsole>
 +
 +The module was detected in the router: “02:00.0” (PCI address of the device: Bus 02, Device 00, Function 0).
 +
 +The device class of the module was correctly identified as “Class 1200” (processing accelerator), i.e., an NPU or AI accelerator
 +
 +The last entry is generated generically because the name of the hardware is not stored in the lspci/pci.ids database.
  
  
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 ===== - Additional information ===== ===== - Additional information =====
  
- * Deepx DX-M1 AI-Chip [[https://deepx.ai/products/dx-m1/#RelatedProducts|Webpage DX-M1 Chip]]+ * Deepx DX-M1 KI-Chip [[https://deepx.ai/products/dx-m1/#RelatedProducts|Webpage DX-M1 Chip]]
  
  * Deepx DX-M1 Documentation [[https://nx.docs.scailable.net/ai-accelerators-support/advanced/deepx-support|DX-M1 Documentation]]  * Deepx DX-M1 Documentation [[https://nx.docs.scailable.net/ai-accelerators-support/advanced/deepx-support|DX-M1 Documentation]]
  
- * AI-Models for the Chip [[https://developer.deepx.ai/modelzoo/| AI-Models]]+ * KI-Models for the Chip [[https://developer.deepx.ai/modelzoo/| KI-Models]]
  
  * Overview  DX-M1 Chip [[https://radxa.com/products/aicore/dx-m1| Overview]]  * Overview  DX-M1 Chip [[https://radxa.com/products/aicore/dx-m1| Overview]]

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app-hotes/ai-features.1782314740.txt.gz · Last modified: 2026/06/24 15:25 by gray